Data Visualization

Matplotlib

Graph 1: Histogram

Histogram to visualize the distribution of a variable.

See Matplotlib Hist

import matplotlib.pyplot as plt
import numpy as np

plt.style.use('_mpl-gallery')

# make data
np.random.seed(1)
x = 4 + np.random.normal(0, 1.5, 200)

# plot:
fig, ax = plt.subplots()

ax.hist(x, bins=8, linewidth=0.5, edgecolor="white")

ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 56), yticks=np.linspace(0, 56, 9))

plt.show()

Seaborn

Graph 2: Nested Boxplot

Box plot to show the distribution of a variable across different categories.

See Nested Boxplot

import seaborn as sns
sns.set_theme(style="ticks", palette="pastel")

# Load the example tips dataset
tips = sns.load_dataset("tips")

# Draw a nested boxplot to show bills by day and time
sns.boxplot(x="day", y="total_bill",
            hue="smoker", palette=["m", "g"],
            data=tips)
sns.despine(offset=10, trim=True)

Plotly

Graph 3: Density heatmaps (2D Histograms)

Density heatmap to visualize the relationship between total bill and tip, considering factors like sex and smoking status.

See Density heatmaps with Plotly Express

import plotly.express as px
import plotly

plotly.offline.init_notebook_mode()

df = px.data.tips()

fig = px.density_heatmap(df, x="total_bill", y="tip", facet_row="sex", facet_col="smoker")
fig.show()

Data Visualization Comparison

Package	Plot Type	Description
Matplotlib	Histogram	Distribution of a variable
Seaborn	Nested Boxplot	Distribution of total bills by day and time, differentiated for smokers and non-smokers
Plotly	Density Heatmap	Relationship between total bill and tip, considering factors like sex and smoking status